Sound recognition technology is widely used in communication systems, for example, applying the sound recognition detection technology in a mobile communication system can improve the traffic processing capacity of the system. In addition, the sound recognition technology is increasingly used in a voice recognition filed, and the technology is already very mature, such as, IBM voice recognition input system ViaVoice, Microsoft voice recognition system SpeechSDK, etc.
With more and more smart phones are used in daily life, voice recognition is also well applied in the smart phones, e.g., iphone has issued a voice recognition application “Google Mobile App”. Another improvement of that voice search is that accents can be selected, and Google can successfully recognize voices from different regions.
Due to the popularity of smart phones, a locating technology is also a hot spot for the application of the smart phone. At present, a scene recognition problem can be solved by making use of antenna-based locating technologies (e.g., WIFI, GSM and GPS) on which study has been widely made. With regard to outdoor locating, GPS has provided very ideal recognition accuracy. However, with regard to indoor locating, there is no ideal and thorough locating solution currently. With the restriction from factors such as internal topology and intense electromagnetic interference inside the building, the antenna signal strength often tends to vary irregularly, thereby making sensing devices unable to perform reasonable location speculation. It is found in study that WIFI signals fluctuate greatly during different periods over a day, and the variations of its strength are not even, and moreover we cannot ensure that the WIFI signals exist in all environments. On the other hand, signals of a base station are more stable at different time periods. However, since the deployment of base stations is not dense enough, there are a lot of difficulties in locating. In addition, such a locating method generally has a high requirement on perfection of infrastructure. However, such costs are undoubtedly high for developing regions. Locating based on GPS, GSM, WIFI signals cannot work in the indoor environment, or has larger locating error, and thus cannot distinguish indoor places geographically close to each other.